[1] Jing Luyang, Zhao Ming*, Li Pin, et al. A Convolutional Neural Network Based Feature Learning and Fault Diagnosis Method for the Condition Monitoring of Gearbox[J]. Measurement, 2017, 111: 1-10. (SCI)(ESI热点论文、ESI高被引论文)
[2] Jing Luyang, Wang Taiyong*, Zhao Ming, et al. An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox[J]. Sensors, 2017, 17(2): 414-429. (SCI)(ESI高被引论文)
[3] Xu Weixiao, Shen Yujie, Jing Luyang*. A Life Prediction Method based on MDFF and DITCN-ABiGRU Mixed Network Model[J]. Heliyon, 2023. (SCI) (已录用)
[4] 张政君,井陆阳*,徐卫晓等.基于时频图与双通道卷积神经网络的轴承故障识别模型[J/OL].机电工程2023:1-10. (中文核心) (已录用)
[5] 王晓昆,井陆阳*,白晓瑞等.仿真数据驱动的起重机钢丝绳断丝定量识别方法[J/OL].机电工程2023:1-10. (中文核心) (已录用)
[6] 徐卫晓*,井陆阳,孙显斌等.基于MDFF和DCNN-SVM混合网络的滚动轴承故障诊断研究[J].制造技术与机床,2023(05):13-20.(中文核心)
[7] 陈荣信,井陆阳*,白晓瑞等.基于残差网络的钢丝绳损伤图像定量识别[J].机床与液压,2023,51(12):24-29.(中文核心)
[8] Zhang Y, Feng Z, Shi S, Dong Z, Zhao L, Jing L*, Tan J. A quantitative identification method based on CWT and CNN for external and inner broken wires of steel wire ropes[J]. Heliyon, 2022, 8(11): e11623. (SCI)
[9] Zhang Y*, Han J, Jing L, Wang C, Zhao L. Intelligent Fault Diagnosis of Broken Wires for Steel Wire Ropes Based on Generative Adversarial Nets. Applied Sciences. 2022, 12(22):11552. (SCI)
[10] Xu Weixiao, Jing Luyang*, Jiwen Tan, et al. A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing [J]. Shock and Vibration, 2020, Article ID 8856818, 12. (SCI)
[11] Zhang Yiqing, Jing Luyang, Tan Jiwen*, et al. A Comparative Study of the Magnetic Concentrating Sensor and the Hall Array Sensor for Damage Detection of Steel Wire Ropes [J]. Materials Research Express , 2020, 9: 1-15 (SCI)
[12] Zhang Yiqing, Jing Luyang*, Xu Weixiao, et al. A Sensor for Broken Wire Detection of Steel Wire Ropes Based on the Magnetic Concentrating Principle[J]. Sensors, 2019, 19(17): 3763-3777. (SCI)
[13] 张立智, 井陆阳*, 徐卫晓, 等. CNN 和 D-S 证据理论相结合的齿轮箱复合故障诊断研究[J]. 机械科学与技术, 2019, 38(10): 1582-1588.(中文核心)
[14] 张立智, 井陆阳*, 徐卫晓, 等. 基于卷积降噪自编码器和CNN的滚动轴承故障诊断[J]. 组合机床与自动化加工技术, 2019, (06): 58-62.(中文核心)
[15] Jing Luyang, Chen Dongxiang, Wang Taiyong*, et al. Research on SVM based Diagnosis System for Oil Tubing[J]. Key Engineering Materials, 2016, 693: 1405-11. (EI)
[16] Jing Luyang,, Wang TaiYong*, Chen Dongxiang, et al. Design and Implementation of Online Monitoring and Remote Diagnostic System for CNC Machine Tools[J]. Advanced Materials Research, 2013, 819: 136-139. (EI)
[17] 井陆阳*, 王太勇, 陈东祥, 等. 数控机床多参数在线监测诊断系统的设计与实现[J]. 制造业自动化, 2013, 35(11): 178-180. (中文核心)
[18] 井陆阳, 王太勇*, 陈东祥, 等. 数控装备微弱故障早期辨识及远程智能维护理论与系统研究[C]. 全国设备监测诊断与维护学术会议、全国设备故障诊断学术会议暨2014年全国设备诊断工程会议, 2014, 33(S).